Senior AI Security Engineer (R-19324)

Responsibilities

• Lead the design, development, and evolution of enterprise-grade security architectures for AI, GenAI, andML platforms, pipelines, and products
• Define and drive security strategy, standards, and reference architectures for AI systems across the organization
• Serve as a technical authority in AI security, advising engineering and leadership teams on secure design, threat mitigation, and risk acceptance decisions
• Implement advanced security controls for LLM-based systems, agentic AI frameworks, and AI-driven APIs at scale
• Lead complex threat modeling, red-teaming, and adversarial testing initiatives targeting AI systems, models, and data ecosystems
• Establish and operationalize controls to mitigate AI-specific risks including prompt injection, data leakage, model exfiltration, model poisoning, and misuse scenarios
• Drive security integration across the AI lifecycle, including model development, training, evaluation, deployment, and runtime operations
• Define and implement secure identity, authentication, authorization, and trust models for human-to-AI and agent-to-agent interactions
• Lead the design of secure AI data architectures, including data governance, lineage protection, and privacy-preserving mechanisms
• Champion DevSecOps practices for AI platforms, embedding automated security testing, validation, and monitoring into CI/CD pipelines
• Collaborate with platform, cloud, and infrastructure teams to ensure secure-by-default environments across multi-cloud ecosystems
• Influence and contribute to enterprise security policies, governance frameworks, and regulatory compliance initiatives related to AI
• Lead incident response and forensic analysis for AI-related security events and vulnerabilities
• Mentor and coach engineers; provide technical leadership across programs and communities of practice
• Drive cross-functional security initiatives, aligning stakeholders across engineering, product, legal, and risk domains
• Stay at the forefront of emerging AI threats, technologies, and industry best practices, and translate insights into actionable improvements

Essential skills and/or Certifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Cybersecurity or related field
• 8 - 12 years of relevant experience, including significant experience in security engineering and deep specialization in AI/ML platforms.
• Deep understanding of application and cloud security, threat modeling, and risk mitigation techniques.
• Proven experience designing and securing large-scale distributed systems, microservices, and API ecosystems
• Advanced expertise in AI/ML security, including LLMs, RAG architectures, vector databases, and agentic frameworks
• Strong knowledge of AI threat models, adversarial AI techniques, and attack vectors (e.g., prompt injection, model manipulation, data poisoning)
• Hands-on experience implementing security controls across data, model, API, and infrastructure layers
• Extensive experience with cloud security (AWS, Azure, GCP) including IAM, network security, and platform services
• Expertise in DevSecOps, automation, and secure SDLC integration
• Experience with containerization, Kubernetes security, and modern infrastructure protection practices
• Ability to define and influence enterprise security standards and architectural decisions
• Strong leadership, stakeholder management, and communication skills
• Experience working across multi-stakeholder, global engineering environments
• Proficiency in Microsoft Office Suites Skills
• Show an ownership mindset in everything you do; be a problem solver, be curious and be inspired to take action, be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
• Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
• Where applicable, fluency in English and languages relevant to the working market.